Contour Integration and Segmentation with a New Lateral Connections Model
Automatically target contour detection from cluttered scenes is a very difficult task for computer vision. Humans, however, have a much better background suppress ability. The preceding models could not implement such a task very well. In this letter, an effective contour integration method based on human visual perception mechanism is proposed. The algorithm combines the properties of primary visual cortex and psychology researching results to simulate the contour perception of the V1 cortex. The new lateral connection based computational model have a better texture suppress ability, while, target’s contour is enhanced. Compared with traditional methods, experiments show that the new method implement a more reasonable simulation of the V1 function structure, availably enhance the target’s contour while suppress the cluttered background, obtain a balance between over and lose detection, besides, it has better accuracy with less computational complexity and time-consuming.
contour enhancement texture suppression horizontal connection visual perception.
Cai Chao
Institute for Pattern Recognition and Artificial Intelligence, The National Key Lab for Multi-spectral Information Processing Technologies, Huazhong University of Science and Technology, Wuhan 430074, China
国际会议
桂林
英文
1-6
2011-11-01（万方平台首次上网日期，不代表论文的发表时间）